Cloud computing is crucial in all areas of data storage and online service delivery. It adds various benefits to the conventional storage and sharing system, such as simple access, on-demand storage, scalability, and cost savings. The employment of its rapidly expanding technologies may give several benefits in protecting the Internet of Things (IoT) and physical cyber systems (CPS) from various cyber threats, with IoT and CPS providing facilities for people in their everyday lives. Because malware (malware) is on the rise and there is no well-known strategy for malware detection, leveraging the cloud environment to identify malware might be a viable way forward. To avoid detection, a new kind of malware employs complex jamming and packing methods. Because of this, it is very hard to identify sophisticated malware using typical detection methods. The article presents a detailed assessment of cloud-based malware detection technologies, as well as insight into understanding the cloud's use in protecting the Internet of Things and critical infrastructure from intrusions. This study examines the benefits and drawbacks of cloud environments in malware detection, as well as presents a methodology for detecting cloud-based malware using deep learning and data extraction and highlights new research on the issues of propagating existing malware. Finally, similarities and variations across detection approaches will be exposed, as well as detection technique flaws. The findings of this work may be utilized to highlight the current issue being tackled in malware research in the future.
{"title":"Enhancing cloud security through the integration of deep learning and data mining techniques: A comprehensive review","authors":"Israa Ezzat salem, Karim Hashim Al-Saedi","doi":"10.21533/pen.v11i3.3596","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3596","url":null,"abstract":"Cloud computing is crucial in all areas of data storage and online service delivery. It adds various benefits to the conventional storage and sharing system, such as simple access, on-demand storage, scalability, and cost savings. The employment of its rapidly expanding technologies may give several benefits in protecting the Internet of Things (IoT) and physical cyber systems (CPS) from various cyber threats, with IoT and CPS providing facilities for people in their everyday lives. Because malware (malware) is on the rise and there is no well-known strategy for malware detection, leveraging the cloud environment to identify malware might be a viable way forward. To avoid detection, a new kind of malware employs complex jamming and packing methods. Because of this, it is very hard to identify sophisticated malware using typical detection methods. The article presents a detailed assessment of cloud-based malware detection technologies, as well as insight into understanding the cloud's use in protecting the Internet of Things and critical infrastructure from intrusions. This study examines the benefits and drawbacks of cloud environments in malware detection, as well as presents a methodology for detecting cloud-based malware using deep learning and data extraction and highlights new research on the issues of propagating existing malware. Finally, similarities and variations across detection approaches will be exposed, as well as detection technique flaws. The findings of this work may be utilized to highlight the current issue being tackled in malware research in the future.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43722965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The issue of transportation in Iraqi cities, particularly Baghdad, is multifaceted and intricate, largely due to the horizontal expansion that puts pressure on services and exacerbates traffic congestion and bottlenecks. The ever-growing population and lack of regulation regarding vehicle imports further compound the situation, making urban transportation in Iraq a challenging problem to address. The digital revolution has ushered in a new era of civilization, marked by significant advancements in communication technology and information systems. This transformation has led to the widespread adoption of communication and information technology in various sectors, including transportation management. However, the successful implementation of digital transportation initiatives requires the collection and organization of extensive data, which is then used to develop graphic and visual software technology, create communication networks, and define new functions for visual and audio files. In this digital age, transportation management has evolved into an interdisciplinary field that leverages the insights from various scientific domains to develop and produce digital maps. The primary objective of digital organization is to recreate reality in a virtual environment, enabling the manipulation of images and the seamless integration of locations beyond geographical boundaries.
{"title":"Enhancing Artificial Intelligence in Advanced Database Systems for Baghdad's Urban Transportation Management","authors":"F. S. Raheem, Alaa Falah Hasan","doi":"10.21533/pen.v11i3.3556","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3556","url":null,"abstract":"The issue of transportation in Iraqi cities, particularly Baghdad, is multifaceted and intricate, largely due to the horizontal expansion that puts pressure on services and exacerbates traffic congestion and bottlenecks. The ever-growing population and lack of regulation regarding vehicle imports further compound the situation, making urban transportation in Iraq a challenging problem to address. The digital revolution has ushered in a new era of civilization, marked by significant advancements in communication technology and information systems. This transformation has led to the widespread adoption of communication and information technology in various sectors, including transportation management. However, the successful implementation of digital transportation initiatives requires the collection and organization of extensive data, which is then used to develop graphic and visual software technology, create communication networks, and define new functions for visual and audio files. In this digital age, transportation management has evolved into an interdisciplinary field that leverages the insights from various scientific domains to develop and produce digital maps. The primary objective of digital organization is to recreate reality in a virtual environment, enabling the manipulation of images and the seamless integration of locations beyond geographical boundaries.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43257533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seba Aziz Sahy, Yi-Ning Niu, Ahmed L. Khalaf, Jamal Fadhil Tawfeq, Ahmed Dheyaa Radhi, Poh Soon JosephNg
Utilizing deep learning algorithms to differentiate the fingerprints of children can greatly enhance their safety. This advanced technology enables precise identification of individual children, facilitating improved monitoring and tracking of their activities and movements. This can effectively prevent abductions and other forms of harm, while also providing a valuable resource for law enforcement and other organizations responsible for safeguarding children. Furthermore, the use of deep learning algorithms minimizes the potential for errors and enhances the overall accuracy of fingerprint recognition. Overall, implementing this technology has immense potential to significantly improve the safety of children in various settings. Our experiments have demonstrated that deep learning significantly enhances the accuracy of fingerprint recognition for children. The model accurately classified fingerprints with an overall accuracy rate of 93%, surpassing traditional fingerprint recognition techniques by a significant margin. Additionally, it correctly identified individual children's fingerprints with an accuracy rate of 89%, showcasing its ability to distinguish between different sets of fingerprints belonging to different children.
{"title":"Enhancing child safety with accurate fingerprint identification using deep learning technology","authors":"Seba Aziz Sahy, Yi-Ning Niu, Ahmed L. Khalaf, Jamal Fadhil Tawfeq, Ahmed Dheyaa Radhi, Poh Soon JosephNg","doi":"10.21533/pen.v11i3.3625","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3625","url":null,"abstract":"Utilizing deep learning algorithms to differentiate the fingerprints of children can greatly enhance their safety. This advanced technology enables precise identification of individual children, facilitating improved monitoring and tracking of their activities and movements. This can effectively prevent abductions and other forms of harm, while also providing a valuable resource for law enforcement and other organizations responsible for safeguarding children. Furthermore, the use of deep learning algorithms minimizes the potential for errors and enhances the overall accuracy of fingerprint recognition. Overall, implementing this technology has immense potential to significantly improve the safety of children in various settings. Our experiments have demonstrated that deep learning significantly enhances the accuracy of fingerprint recognition for children. The model accurately classified fingerprints with an overall accuracy rate of 93%, surpassing traditional fingerprint recognition techniques by a significant margin. Additionally, it correctly identified individual children's fingerprints with an accuracy rate of 89%, showcasing its ability to distinguish between different sets of fingerprints belonging to different children.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44401266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research paper studies the status and condition of the green areas in the city of Erbil, for this purpose all green areas in the city (763 plots) and all population number according to 12 sectors are collected according to their locations and are analyzed spatially by GIS program (Moran I). Researchers have proved that distribution of green areas is random. Moreover, this distribution is not based on the urban planning basics and its criteria: green area per person (GAPP) and green area to the city ratio (GAR) also not based on the basics of urban planning for two criteria , GAPP is optimized from 9.3 to 14 and GAR optimized from 0.06 to 0.09 while the equilateral tringle adopted as optimum distribution for green area units GAU, for 12 sectors adopted combined standards together and the solution was the population density ratio must be 0.01 or less, to obtain criteria and this must preserved and adhered to the planning and laws and regulations strictly. This method can be applied to the study of the spatial distribution in order to compare it with the distribution of schools, health centers and other services or infrastructures.
{"title":"Optimization of the Urban Green Area in Erbil Territory for Sustainable Development","authors":"Azad Arshad Abdul Wahab, M. Jassim","doi":"10.21533/pen.v11i3.3555","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3555","url":null,"abstract":"This research paper studies the status and condition of the green areas in the city of Erbil, for this purpose all green areas in the city (763 plots) and all population number according to 12 sectors are collected according to their locations and are analyzed spatially by GIS program (Moran I). Researchers have proved that distribution of green areas is random. Moreover, this distribution is not based on the urban planning basics and its criteria: green area per person (GAPP) and green area to the city ratio (GAR) also not based on the basics of urban planning for two criteria , GAPP is optimized from 9.3 to 14 and GAR optimized from 0.06 to 0.09 while the equilateral tringle adopted as optimum distribution for green area units GAU, for 12 sectors adopted combined standards together and the solution was the population density ratio must be 0.01 or less, to obtain criteria and this must preserved and adhered to the planning and laws and regulations strictly. This method can be applied to the study of the spatial distribution in order to compare it with the distribution of schools, health centers and other services or infrastructures.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49595143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Azmi Shawkat Abdulbaqi, Hussein Ali Hussein Al Naffakh, Sura Abdulmunem Mohammed Al-Juboori, Ahmed Dheyaa Radhi, Jamal Fadhil Tawfeq, Poh Soon JosephNg
In the research, a software for ECG signal based on Chaos encryption based on C#-programmed and Kit of Microsoft Visual Studio Development was implemented. A chaos logic map (ChLMp ) and its initial value are utilized to create Level-1 ECG signal based on Chaos encryption bit streams. A ChLMp, an initial value, a ChLMp bifurcation parameter, and two encryption level parameters are utilized to create level-2 ECG signal based on Chaos encryption bit streams. The level-3 ECG signal based on Chaos encryption software utilizes two parameters for the level of encryption, a permutation mechanism, an initial value, a bifurcation parameter of the level of encryption
{"title":"Exploring the potential of offline cryptography techniques for securing ECG signals in healthcare","authors":"Azmi Shawkat Abdulbaqi, Hussein Ali Hussein Al Naffakh, Sura Abdulmunem Mohammed Al-Juboori, Ahmed Dheyaa Radhi, Jamal Fadhil Tawfeq, Poh Soon JosephNg","doi":"10.21533/pen.v11i3.3604","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3604","url":null,"abstract":"In the research, a software for ECG signal based on Chaos encryption based on C#-programmed and Kit of Microsoft Visual Studio Development was implemented. A chaos logic map (ChLMp ) and its initial value are utilized to create Level-1 ECG signal based on Chaos encryption bit streams. A ChLMp, an initial value, a ChLMp bifurcation parameter, and two encryption level parameters are utilized to create level-2 ECG signal based on Chaos encryption bit streams. The level-3 ECG signal based on Chaos encryption software utilizes two parameters for the level of encryption, a permutation mechanism, an initial value, a bifurcation parameter of the level of encryption","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48041110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. S. Jabbar, Israa Ibraheem Al_Barazanchi, Ahmed L. Khalaf, Poh Soon JosephNg, Ahmed Dheyaa Radhi
The study presented in this research focuses on linearization strategies for compensating for nonlinearity in RF front ends in multi-antenna M-MIMO OFDM communication systems. The study includes the design and evaluation of techniques such as analogue pre-distortion (APD), crest factor reduction (CFR), multi-antenna clipping noise cancellation (M-CNC), and multi-clipping noise cancellation (MCNC). Nonlinearities in RF front ends can cause signal distortion, leading to reduced system performance. To address this issue, various linearization methods have been proposed. This research examines the impact of antenna correlation on power amplifier efficiency and bit error rate (BER) of transmissions using these methods. Simulation studies conducted under high signal-to-noise ratio (SNR) regimes reveal that M-CNC and MCNC approaches offer significant improvement in BER performance and PA efficiency compared to other techniques. Additionally, the study explores the influence of clipping level and antenna correlation on the effectiveness of these methods. The findings suggest that appropriate linearization strategies should be selected based on factors such as the number of antennas, SNR, and clipping level of the system.
{"title":"Optimizing multi-antenna M-MIMO DM communication systems with advanced linearization techniques for RF front-end nonlinearity compensation in a comprehensive design and performance evaluation study","authors":"M. S. Jabbar, Israa Ibraheem Al_Barazanchi, Ahmed L. Khalaf, Poh Soon JosephNg, Ahmed Dheyaa Radhi","doi":"10.21533/pen.v11i3.3609","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3609","url":null,"abstract":"The study presented in this research focuses on linearization strategies for compensating for nonlinearity in RF front ends in multi-antenna M-MIMO OFDM communication systems. The study includes the design and evaluation of techniques such as analogue pre-distortion (APD), crest factor reduction (CFR), multi-antenna clipping noise cancellation (M-CNC), and multi-clipping noise cancellation (MCNC). Nonlinearities in RF front ends can cause signal distortion, leading to reduced system performance. To address this issue, various linearization methods have been proposed. This research examines the impact of antenna correlation on power amplifier efficiency and bit error rate (BER) of transmissions using these methods. Simulation studies conducted under high signal-to-noise ratio (SNR) regimes reveal that M-CNC and MCNC approaches offer significant improvement in BER performance and PA efficiency compared to other techniques. Additionally, the study explores the influence of clipping level and antenna correlation on the effectiveness of these methods. The findings suggest that appropriate linearization strategies should be selected based on factors such as the number of antennas, SNR, and clipping level of the system.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48755141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although using rubber to create reinforced concrete substrates has many benefits, using rubberized concrete substrates, such as beams, is still limited. Where concrete with rubber included in it starts to lose a percentage of its mechanical qualities, such as flexural strength. Conversely, a significant portion of structural uses for strengthening reinforced concrete beams using exterior carbon fiber reinforced polymer (CFRP) sheets are for flexural strengthening. This study used externally bonded carbon fiber-reinforced polymer (CFRP) sheets to compensate for the reduction in flexural strength when creating rubberized concrete beams. The reinforced concrete beams used in this study were divided into three groups, each with three beams. Waste tire rubber was replaced (5%) of the fine aggregate volume in the first group and replaced (10%) in the second group. The reference group consists of the third set of beams. The first concrete beam in any group was always devoid of external strengthening, the second beam had one layer and the third beam had two layers of (CFRP) sheet. The third layer of strengthening was numerically represented using ABAQUS, a finite element analysis program. The results indicate that for two-volume replacement rates of fine aggregate (5 and 10) %, a decrease in ductility will have been accompanied by an improvement in the flexural strength of the rubberized concrete beam when externally strengthening with one, two, and three layers of (CFRP) sheets.
{"title":"Flexural behavior of CFRP-strengthened reinforced concrete beams rubberized with finely minced rubber tire","authors":"Adnan Abdullah Adday, Ahmed Sultan Ali","doi":"10.21533/pen.v11i3.3597","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3597","url":null,"abstract":"Although using rubber to create reinforced concrete substrates has many benefits, using rubberized concrete substrates, such as beams, is still limited. Where concrete with rubber included in it starts to lose a percentage of its mechanical qualities, such as flexural strength. Conversely, a significant portion of structural uses for strengthening reinforced concrete beams using exterior carbon fiber reinforced polymer (CFRP) sheets are for flexural strengthening. This study used externally bonded carbon fiber-reinforced polymer (CFRP) sheets to compensate for the reduction in flexural strength when creating rubberized concrete beams. The reinforced concrete beams used in this study were divided into three groups, each with three beams. Waste tire rubber was replaced (5%) of the fine aggregate volume in the first group and replaced (10%) in the second group. The reference group consists of the third set of beams. The first concrete beam in any group was always devoid of external strengthening, the second beam had one layer and the third beam had two layers of (CFRP) sheet. The third layer of strengthening was numerically represented using ABAQUS, a finite element analysis program. The results indicate that for two-volume replacement rates of fine aggregate (5 and 10) %, a decrease in ductility will have been accompanied by an improvement in the flexural strength of the rubberized concrete beam when externally strengthening with one, two, and three layers of (CFRP) sheets.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47903473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Najwan Abed Hasan, Azhar M. Kadim, Haider M. Jaber, Aseel B. Alnajjar, Mohammed Sahib Mahdi Altaei
In this paper, we propose an efficient image hiding method that combines image encryption and chaotic mapping to introduce adaptive data hiding for improving the security and robustness of image data hiding in cover audio. The feasibility of using chaotic maps to hide encrypted image in the high frequency band of the audio is investigated. The proposed method was based on hiding the image data in the noisiest part of the audio, which is the high frequency band that was extracted by the zero crossing filter. Six types of digital images were used, each of size fit the length of used audio, this to facilitate the process of hiding them among the audio samples. The input image was encrypted by a one-time pad method, then its bits were hidden in the audio by the chaotic map. The process of retrieving the image from the audio was in the opposite way, where the image data was extracted from the high frequency band of the audio file, and then the extracted image was decrypted to produce the retrieved image. Four qualitative metrics were used to evaluate the hiding method in two paths: the first depends on comparing the retrieved image with the original image, while the second depends on comparing the audio containing the image data with the original audio once, and another time by comparing the cover audio with the original audio. The results of the quality metrics proved the efficiency of the proposed method, and it showed a slight and unnoticed effect between the research materials, which indicates the success of the hiding process and the validity of the research path.
{"title":"Image hiding in audio file using chaotic method","authors":"Najwan Abed Hasan, Azhar M. Kadim, Haider M. Jaber, Aseel B. Alnajjar, Mohammed Sahib Mahdi Altaei","doi":"10.21533/pen.v11i3.3642","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3642","url":null,"abstract":"In this paper, we propose an efficient image hiding method that combines image encryption and chaotic mapping to introduce adaptive data hiding for improving the security and robustness of image data hiding in cover audio. The feasibility of using chaotic maps to hide encrypted image in the high frequency band of the audio is investigated. The proposed method was based on hiding the image data in the noisiest part of the audio, which is the high frequency band that was extracted by the zero crossing filter. Six types of digital images were used, each of size fit the length of used audio, this to facilitate the process of hiding them among the audio samples. The input image was encrypted by a one-time pad method, then its bits were hidden in the audio by the chaotic map. The process of retrieving the image from the audio was in the opposite way, where the image data was extracted from the high frequency band of the audio file, and then the extracted image was decrypted to produce the retrieved image. Four qualitative metrics were used to evaluate the hiding method in two paths: the first depends on comparing the retrieved image with the original image, while the second depends on comparing the audio containing the image data with the original audio once, and another time by comparing the cover audio with the original audio. The results of the quality metrics proved the efficiency of the proposed method, and it showed a slight and unnoticed effect between the research materials, which indicates the success of the hiding process and the validity of the research path.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43842687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The forecasting using the multi-layered neural network model is one of the methods used recently in forecasting, especially in climate forecasts for certain regions, because of its accuracy in forecasting, which sometimes reaches levels close to the real collected data. In this research, the daily temperatures in the climate of Iraq were predicted, by taking data from the Iraqi Meteorological Authority by (228) observations, which represent the daily temperatures of Karbala Governorate in the year (2021), The results of the autocorrelation and partial autocorrelation showed that the daily temperature series of Karbala governorate is unstable, and this was confirmed by conducting the augmented Dickey Fuller test. The data was analyzed using the multi-layered neural network model in two stages, and it was later shown that the accuracy of estimation and prediction using the multi-layered neural network even if the time series is not stable, The results showed an indication of an rising increase in temperatures during the coming years. The researcher concluded that it is necessary to pay attention to the vegetation cover and to conduct many predictive studies of the climate using the multi-layered neural network.
{"title":"Estimation and prediction of temperature in Iraq using the multi-layered neural network model","authors":"R. Al-saffar, M. Neamah, Eman Raed Hamza","doi":"10.21533/pen.v11i3.3620","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3620","url":null,"abstract":"The forecasting using the multi-layered neural network model is one of the methods used recently in forecasting, especially in climate forecasts for certain regions, because of its accuracy in forecasting, which sometimes reaches levels close to the real collected data. In this research, the daily temperatures in the climate of Iraq were predicted, by taking data from the Iraqi Meteorological Authority by (228) observations, which represent the daily temperatures of Karbala Governorate in the year (2021), The results of the autocorrelation and partial autocorrelation showed that the daily temperature series of Karbala governorate is unstable, and this was confirmed by conducting the augmented Dickey Fuller test. The data was analyzed using the multi-layered neural network model in two stages, and it was later shown that the accuracy of estimation and prediction using the multi-layered neural network even if the time series is not stable, The results showed an indication of an rising increase in temperatures during the coming years. The researcher concluded that it is necessary to pay attention to the vegetation cover and to conduct many predictive studies of the climate using the multi-layered neural network.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45992701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adherence to treatment plans as per the prescribed medication pattern is essential to ensure better treatment outcomes. However, unfortunately, a large sum of patients often disregards this area and tend to show non-compliance to this behavior, leading towards worst treatment scenarios. The current work is dedicated to the evaluation of prescribed medication patterns and adherence to treatment plans among breast cancer patients. The study is designed on a survey approach. The study sample involved 80 participants (55 breast cancer patients and 25 breast surgeons) enrolled at the King Hussein Cancer Center (KHCC) in Amman, Jordan. In order to accumulate the required data, a questionnaire was designed and sent to the respondents in KHCC. The respondents were asked to reflect on their experience and identify the primary aspects leading to non-adherence to treatment plans among patients. After separately analyzing the questionnaires’, responses submitted by the patients and surgeons, it was noted that patients consider psychological and social factors to be the primary cause of non-adherence behavior, whereas the surgeons attributed this behavior as a result of medication side effects and the complexity of treatments. Hence, it has been concluded that consideration must be paid to alleviating the aspects leading towards these causes so as to ensure patients’ maximum participation in their medication plans and augment the efficacy of therapies.
{"title":"Evaluation of prescribed medication pattern and adherence to treatment plans among breast cancer patients at KHCC","authors":"Zainab Zakaraya, Et al.","doi":"10.21533/pen.v11i3.3675","DOIUrl":"https://doi.org/10.21533/pen.v11i3.3675","url":null,"abstract":"Adherence to treatment plans as per the prescribed medication pattern is essential to ensure better treatment outcomes. However, unfortunately, a large sum of patients often disregards this area and tend to show non-compliance to this behavior, leading towards worst treatment scenarios. The current work is dedicated to the evaluation of prescribed medication patterns and adherence to treatment plans among breast cancer patients. The study is designed on a survey approach. The study sample involved 80 participants (55 breast cancer patients and 25 breast surgeons) enrolled at the King Hussein Cancer Center (KHCC) in Amman, Jordan. In order to accumulate the required data, a questionnaire was designed and sent to the respondents in KHCC. The respondents were asked to reflect on their experience and identify the primary aspects leading to non-adherence to treatment plans among patients. After separately analyzing the questionnaires’, responses submitted by the patients and surgeons, it was noted that patients consider psychological and social factors to be the primary cause of non-adherence behavior, whereas the surgeons attributed this behavior as a result of medication side effects and the complexity of treatments. Hence, it has been concluded that consideration must be paid to alleviating the aspects leading towards these causes so as to ensure patients’ maximum participation in their medication plans and augment the efficacy of therapies.","PeriodicalId":37519,"journal":{"name":"Periodicals of Engineering and Natural Sciences","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41591405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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